IPA & Thematic analysis
Could anyone make a clear distinction between IPA and Thematic analysis in psychology?
Posted in: Methodology
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Anmar Bishara
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Could anyone make a clear distinction between IPA and Thematic analysis in psychology?
Posted in: Methodology
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Robert Taylor 2:09 am on December 18, 2016 Permalink | Log in to Reply
Interpretative phenomenological analysis (IPA) and thematic analysis both can be used to analyse most types of qualitative data such as interviews, focus groups, diaries, qualitative surveys, secondary sources, vignettes, story completion tasks etc. The basic difference is that coding in TA begins after a process of data familiarization, in which the researcher notes any initial analytic observations about each data item and the entire data-set. Coding in IPA consists of a process of ‘initial commenting’ or ‘initial noting,’ in which the researcher writes their initial analytic observations about the data on the data item.
bridgette6020 12:45 pm on December 19, 2016 Permalink | Log in to Reply
In IPA, researcher codes his first data and develops themes for it instead of first coding the entire data, which happens in thematic analysis. Also, two levels of theme development involved in IPA but only one in theme analysis. Google it for I do not have much knowledge about these levels.
Anmar Bishara 11:11 am on December 20, 2016 Permalink | Log in to Reply
Okay, I will do that but thanks for briefing. Does the result yielded through both methods differ?
bridgette6020 10:14 am on December 21, 2016 Permalink | Log in to Reply
Not much. Similar results are likely to be obtained. Analytic methods do effect but not much since the concept remains same.
Anmar Bishara 6:17 am on December 22, 2016 Permalink | Log in to Reply
But the question remains same. Which is better?
Robert Taylor 7:18 am on December 23, 2016 Permalink | Log in to Reply
I would suggest thematic analysis when you want to use data that do not capture first-person accounts of personal experiences (such as focus groups or story completion tasks), and when working with larger samples.